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Sobre

J. T. Saraiva nasceu no Porto, Portugal, em 1962 e obteve um grau equivalente a MSc, o PhD e o título de Agregado pela Faculdade de Engenharia da Universidade do Porto em 1987, 1993 e 2002 onde é actualmente Professor. Intergra o INESC Porto desde 1985 onde é Investigador Sénior e colaborou ou foi responsável por diversas actividades no âmbito de projectos financiados pela EU, projectos financiandos por entidades nacionais bem diversos contratos de consultoria técnica por exemplo envolvendo a Entidade Reguladora dos Serviços Energéticos, a EDP Distribuição, a EDP Produção, a REN, a Empresa de Electricidade da Madeira, a Empresa de Electricidade dos Açores e os Operadores do Ssitema Eléctrico Grego e Brasileiro. Ao longo da sua carreira académica orientou mais de 50 Teses de Mestrado, 10 teses de Doutoramento e foi co-autor de 3 livros, de mais de 30 publicações em international journals e mais de 120 publicações em conferências internacionais.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    João Tomé Saraiva
  • Cluster

    Energia
  • Cargo

    Investigador Coordenador
  • Desde

    15 julho 1985
018
Publicações

2020

A two-stage strategy for security-constrained AC dynamic transmission expansion planning

Autores
Gomes, PV; Saraiva, JT;

Publicação
Electric Power Systems Research

Abstract
This paper presents a new and promising strategy organized in two stages to solve the dynamic multiyear transmission expansion planning, TEP, problem. Specifically, the first stage is related to the reduction of the search space size and it is conducted by a novel constructive heuristic algorithm (CHA). The second one is responsible for the refinement of the optimal solution plan and it uses a novel evolutionary algorithm based on the best features of particle swarm optimization (PSO) and genetic algorithm (GA). The planning problem is modelled as a dynamic and multiyear approach to ensure that it keeps a holistic view over the entire planning horizon and it aims at minimizing the total system costs comprising the investment and operation costs. Additionally, the N-1 contingency criterion is also considered in the problem. The developed approach was tested using the IEEE 118-Bus test system and the obtained results demonstrate its advantages in terms of efficiency and required computational time. Furthermore, the results demonstrated that the novel strategy can enable the utilization of the AC optimal power flow (OPF) in a faster and reliable way when compared to the standard and widespread DC-OPF model. © 2019 Elsevier B.V.

2019

State-of-the-art of transmission expansion planning: A survey from restructuring to renewable and distributed electricity markets

Autores
Gomes, PV; Saraiva, JT;

Publicação
International Journal of Electrical Power and Energy Systems

Abstract
Transmission Expansion Planning (TEP) problem aims at identifying when and where new equipment as transmission lines, cables and transformers should be inserted on the grid. The transmission upgrade capacity is motivated by several factors as meeting the increasing electricity demand, increasing the reliability of the system and providing non-discriminatory access to cheap generation for consumers. However, TEP problems have been changing over the years as the electrical system evolves. In this way, this paper provides a detailed historical analysis of the evolution of the TEP over the years and the prospects for this challenging task. Furthermore, this study presents an outline review of more than 140 recent articles about TEP problems, literature insights and identified gaps as a critical thinking in how new tools and approaches on TEP can contribute for the new era of renewable and distributed electricity markets. © 2019 Elsevier Ltd

2019

Impact of decision-making models in Transmission Expansion Planning considering large shares of renewable energy sources

Autores
Gomes, PV; Saraiva, JT; Carvalho, L; Dias, B; Oliveira, LW;

Publicação
Electric Power Systems Research

Abstract

2019

On the use of causality inference in designing tariffs to implement more effective behavioral demand response programs

Autores
Ganesan, K; Saraiva, JT; Bessa, RJ;

Publicação
Energies

Abstract
Providing a price tariff that matches the randomized behavior of residential consumers is one of the major barriers to demand response (DR) implementation. The current trend of DR products provided by aggregators or retailers are not consumer-specific, which poses additional barriers for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causality inference between DR tariffs and observed residential electricity consumption to estimate consumers’ consumption elasticity. It determines the flexibility of each client under the considered DR program and identifies whether the tariffs offered by the DR program affect the consumers’ usual consumption or not. The aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs. We identify a set of critical clients who actively participate in DR events along with the most responsive and least responsive clients for the considered DR program. We find that the percentage of DR consumers who actively participate seem to be much less than expected by retailers, indicating that not all consumers’ elasticity is effectively utilized. © 2019 by the authors.

2019

Using causal inference to measure residential consumers demand response elasticity

Autores
Ganesan, K; Saraiva, JT; Bessa, RJ;

Publicação
2019 IEEE Milan PowerTech, PowerTech 2019

Abstract
Engaging the residential consumers and providing the best tariffs for their randomized behavior is one of the major barriers to demand response (DR) implementation. Additionally, DR offers submitted by aggregators or retailers are not consumer-specific, which turns it even more difficult for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causal inference between dynamic DR tariffs and observed residential electricity consumption (resolution of 30 minutes) to estimate consumers' consumption elasticity. Ultimately, the aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs. © 2019 IEEE.

Teses
supervisionadas

2019

Residential Consumer Behavioural Analysis on the participation in Demand Response Strategies including distributed generation and electric vehicles

Autor
Kamalanathan Ganesan

Instituição
UP-FEUP

2019

Multi-objective long-term transmission expansion planning

Autor
Luiz Eduardo de Oliveira

Instituição
UP-FEUP

2019

Economic and Regulatory Schemes to Maximize the Social Benefit of Energy Communities

Autor
Rogério Rui Dias da Rocha

Instituição
UP-FEUP

2019

Estimativa do Impacto da Presença de Dispositivos de Armazenamento nos Preços de Mercado

Autor
André Rodrigues de Oliveira

Instituição
UP-FEUP

2019

Análise do Comportamento dos Preços do Mercado Ibérico no ano de 2018

Autor
Diana Beatriz Teixeira da Silva Pereira

Instituição
UP-FEUP